SQL Server to Redshift Migration Unblocked in 8 Days
A stalled financial services migration rescued through AI-powered reverse engineering, fact-based planning, and automated legacy intelligence.
Key Metrics
8 Days - Discovery to Delivery
90%+ - Time Saved on Discovery
100% - Objects Documented
0 - SME Dependency
THE CHALLENGE
A Brazilian system integrator was engaged by a financial services institution to modernize their legacy SQL Server 2015 data warehouse to AWS Redshift. The project stalled before migration could begin. Hundreds of undocumented stored procedures, views, and ETL scripts built by departed engineers meant the team had no visibility into what existed, how it connected, or what business logic was embedded in the code. Without this understanding, they could not define a migration roadmap, produce credible estimates, or anticipate technical blockers.
PAIN POINTS
✖ Zero documentation on data models, stored procedures, and ETL logic across the entire estate
✖ Original engineers departed with no SMEs available for knowledge transfer
✖ No visibility into object dependencies, making migration wave planning impossible
✖ T-SQL constructs with no direct Redshift equivalent, creating unknown conversion risk
✖ Traditional reverse engineering would take months with a large specialized team
THE SOLUTION
3X Data Engineering’s Reverse Engineering Engine connected directly to the SQL Server 2015 environment with read-only access and performed automated extraction, semantic analysis, and documentation of every database object. Combined with the Metadata Intelligence Engine and Fact-Based Estimation Engine, it delivered a comprehensive Migration Canvas in 8 business days.
SOLUTION HIGHLIGHTS
✓ Source-connected discovery with automated extraction of all tables, views, stored procedures, functions, and triggers
✓ AI-powered deconstruction of every SQL object to extract business logic, transformation rules, and data flow patterns
✓ Object-level complexity scoring based on T-SQL constructs, Redshift compatibility, and interdependencies
✓ T-SQL to Redshift gap analysis with flagged incompatibilities and recommended workarounds
✓ Dependency and lineage mapping revealing hidden connections critical for migration wave planning
✓ Fact-based effort estimates, phased roadmap, skills matrix, and risk register
RESULTS
| Traditional Approach | With 3X Data Engineering | |
|---|---|---|
| Discovery Phase | 6–18 weeks | 8 business days |
| Team Required | 5+ specialists | Lean expert team |
| Discovery Effort | Months of manual work | Automated in days |
| SME Dependency | Critical blocker | Zero dependency |
| Documentation | Manual interviews | Auto generated |
| Effort Estimates | Assumption-based | Fact-based, per-object |
DELIVERY TIMELINE
DAYS 1–2: Discover: Secure connection, automated extraction of all database objects, full estate catalogued
DAYS 3–6: Analyze: AI-powered deconstruction, complexity scoring, T-SQL gap analysis, lineage mapping
DAYS 7–8: Deliver: Migration Canvas handover, phased roadmap, skills matrix, knowledge transfer session
ACCELERATORS USED
3X Reverse Engineer: Legacy system deconstruction
3X Metadata Intelligence: Automated metadata discovery
3X Code Conversion: T-SQL gap analysis